Static split parser

A header only "csv" parser which is fast and versatile with modern C++ api. Requires compiler with C++17 support.

Conversion for numeric values taken from Oliver Schönrock .
Function traits taken from qt-creator .

Example

Lets say we have a csv file containing students in the following format <name,age,grade>:

$ cat students.csv
James Bailey,65,2.5
Brian S. Wolfe,40,11.9
Nathan Fielder,37,Really good grades
Bill (Heath) Gates,65,3.3

#include <iostream>
#include <ss/parser.hpp>

int main() {
    ss::parser p{"students.csv", ","};
    if (!p.valid()) {
        std::cout << p.error_msg() << std::endl;
        exit(EXIT_FAILURE);
    }

    while (!p.eof()) {
        auto [name, age, grade] = p.get_next<std::string, int, double>();

        if (p.valid()) {
            std::cout << name << ' ' << age << ' ' << grade << std::endl;
        }
    }

    return 0;
}

And if we compile and execute the program we get the following output:

$ ./a.out
James Bailey 65 2.5
Brian S. Wolfe 40 11.9
Bill (Heath) Gates 65 3.3

Features

• Works on any type
• Easy to use
• No exceptions
• Columns and rows can be ignored
• Works with any type of delimiter
• Can return whole objects composed of converted values
• Descriptive error handling can be enabled
• Restrictions can be added for each column
• Works with std::optional and std::variant
• Works with CRLF and LF
• Conversions can be chained if invalid
• Fast

Instalation

$ git clone https://github.com/red0124/ssp
$ cd ssp
$ sudo make install

Run tests (optional):

$ make test

Usage

Error handling

Detailed error messages can be accessed via the error_msg method, and to
enable them the error mode has to be changed to error_mode::error_string using
the set_error_mode method:

void parser::set_error_mode(ss::error_mode);
const std::string& parser::error_msg();
bool parser::valid();
bool parser::eof();

Error messages can always be disabled by setting the error mode to
error_mode::error_bool. An error can be detected using the valid method which
would return false if the file could not be opened, or if the conversion
could not be made (invalid types, invalid number of columns, ...).
The eof method can be used to detect if the end of the file was reached.

Conversions

The above example will be used to show some of the features of the library.
As seen above, the get_next method returns a tuple of objects specified
inside the template type list.

If a conversion could not be applied, the method would return a tuple of
default constructed objects, and valid would return false, for example
if the third (grade) column in our csv could not be converted to a double
the conversion would fail.

If get_next is called with a tuple it would behave identically to passing
the same tuple parameters to get_next:

using student = std::tuple<std::string, int, double>;

// returns std::tuple<std::string, int, double>
auto [name, age, grade] = p.get_next<student>();

Note, it does not always return a student tuple since the returned tuples
parameters may be altered as explained below (no void, no restrictions, ...)

Whole objects can be returned using the get_object function which takes the
tuple, created in a similar way as get_next does it, and creates an object
out of it:

struct student {
    std::string name;
    int age;
    double grade;
};

// returns student
auto student = p.get_object<student, std::string, int, double>();

This works with any object if the constructor could be invoked using the
template arguments given to get_object:

// returns std::vector<std::string> containing 3 elements
auto vec = p.get_object<std::vector<std::string>, std::string, std::string, 
                        std::string>();

And finally, using something I personally like to do, a struct (class) with a tied
method witch returns a tuple of references to to the members of the struct.

struct student {
    std::string name;
    int age;
    double grade;

    auto tied() { return std::tie(name, age, grade); }
};

The method can be used to compare the object, serialize it, deserialize it, etc.
Now get_next can accept such a struct and deduce the types to which to convert the csv.

// returns student
auto s = p.get_next<student>();

Note, the order in which the members of the tied method are returned must
match the order of the elements in the csv

Special types

Passing void makes the parser ignore a column.
In the given example void could be given as the second
template parameter to ignore the second (age) column in the csv, a tuple
of only 2 parameters would be retuned:

// returns std::tuple<std::string, double>
auto [name, grade] = p.get_next<std::string, void, double>();

Works with different types of conversions too:

using student = std::tuple<std::string, void, double>;

// returns std::tuple<std::string, double>
auto [name, grade] = p.get_next<student>();

To ignore a whole row, ignore_next could be used, returns false if eof:

bool parser::ignore_next();

std::optional could be passed if we wanted the conversion to proceed in the
case of a failure returning std::nullopt for the specified column:

// returns std::tuple<std::string, int, std::optional<double>>
auto [name, age, grade] = p.get_next<std::string, int, std::optional<double>();
if(grade) {
    // do something with grade
}

Similar to std::optional, std::variant could be used to try other
conversions if the previous failed (Note, conversion to std::string will
always pass):

// returns std::tuple<std::string, int, std::variant<double, char>>
auto [name, age, grade] = 
    p.get_next<std::string, int, std::variant<double, char>();
if(std::holds_alternative<double>(grade)) {
    // grade set as double
} else if(std::holds_alternative<char>(grade)) {
    // grade set as char
}

Restrictions

Custom restrictions can be used to narrow down the conversions of unwanted
values. ss::ir (in range) and ss::ne (none empty) are one of those:

// ss::ne makes sure that the name is not empty
// ss::ir makes sure that the grade will be in range [0, 10]
// returns std::tuple<std::string, int, double>
auto [name, age, grade] = 
    p.get_next<ss::ne<std::string>, int, ss::ir<double, 0, 10>>();

If the restrictions are not met, the conversion will fail.
Other predefined restrictions are ss::ax (all except), ss::nx (none except)
and ss::oor (out of range):

// all ints exept 10 and 20
ss::ax<int, 10, 20>
// only 10 and 20
ss::nx<int, 10, 20>
// all values except the range [0, 10]
ss::oor<int, 0, 10>

To define a restriction, a class/struct needs to be made which has a
ss_valid method which returns a bool and accepts one object. The type of the
conversion will be the same as the type of the passed object within ss_valid
and not the restriction itself. Optionally, an error method can be made to
describe the invalid conversion.

template <typename T>
struct even {
    bool ss_valid(const T& value) const {
        return value % 2 == 0;
    }

    // optional
    const char* error() const {
        return "number not even";
    }
};

// only even numbers will pass
// returns std::tuple<std::string, int>
auto [name, age] = p.get_next<std::string, even<int>, void>();

Custom conversions

Custom types can be used when converting values. An override of the ss::extract
function needs to be made and you are good to go. Custom conversion for an enum
would look like this:

enum class shape { circle, rectangle, triangle };

template <>
inline bool ss::extract(const char* begin, const char* end, shape& dst) {
    const static std::unordered_map<std::string, shape>
        shapes{{"circle", shape::circle},
               {"rectangle", shape::rectangle},
               {"triangle", shape::triangle}};

    if (auto it = shapes.find(std::string(begin, end)); it != shapes.end()) {
        dst = it->second;
        return true;
    }
    return false;
}

The shape enum will be in an example below. The inline is there just to prevent
multiple definition errors. The function returns true if the conversion was
a success, and false otherwise. The function uses const char* begin and end
for performance reasons.